Triple

T14295420
Position Surface form Disambiguated ID Type / Status
Subject Northern Berlin E354425 entity
Predicate hasPart P35 FINISHED
Object Niederschönhausen E412020 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Niederschönhausen | Statement: [Northern Berlin, hasPart, Niederschönhausen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Niederschönhausen
Context triple: [Northern Berlin, hasPart, Niederschönhausen]
  • A. Niederschönhausen chosen
    Niederschönhausen is a residential district in the Berlin borough of Pankow, known for its historic villas, green spaces, and the former presidential residence Schloss Schönhausen.
  • B. Niederschöneweide
    Niederschöneweide is a locality in the Berlin borough of Treptow-Köpenick, known for its riverside setting along the Spree and its mix of residential areas and former industrial sites.
  • C. Schönewalde
    Schönewalde is a town in the state of Brandenburg, Germany, known for hosting a German Air Force base.
  • D. Wilhelmsdorf
    Wilhelmsdorf is a village-level subdivision of the town of Usingen in the Hochtaunus district of Hesse, Germany.
  • E. Schönwalde
    Schönwalde is a locality within the municipality of Wandlitz in the state of Brandenburg, Germany.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d8278e17088190b328c5a9d4be74ff completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de717b35ec81908968994e65737c66 completed April 14, 2026, 4:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe8bbd051c8190a89f9801a7b08b2d completed May 9, 2026, 1:19 a.m.
Created at: April 10, 2026, 1:11 a.m.